Field
This disclosure relates to data processing of X-ray projection data obtained using spectrally-resolving photon-counting X-ray detectors for both computed tomography (CT) and non-CT applications, and more particularly relates to the data processing steps of calibration, correcting for detector artifacts, measurement artifacts, and performing material decomposition of X-ray projection data.
Description of the Related Art
Computed tomography (CT) systems and methods are widely used, particularly for medical imaging and diagnosis. CT systems generally create images of one or more sectional slices through a subject's body. A radiation source, such as an X-ray source, irradiates the body from one side. A collimator, generally adjacent to the X-ray source, limits the angular extent of the X-ray beam, so that radiation impinging on the body is substantially confined to a planar region defining a cross-sectional slice of the body. At least one detector (and generally many more than one detector) on the opposite side of the body receives radiation transmitted through the body substantially in the plane of the slice. The attenuation of the radiation that has passed through the body is measured by processing electrical signals received from the detector.
Conventionally, energy-integrating detectors have been used to measure CT projection data. Now, recent technological developments are making photon-counting detectors a feasible alternative to conventional energy-integrating detectors. Photon-counting detectors have many advantages including their capacity for preforming spectral CT. To obtain the spectral nature of the transmitted X-ray data, the photon-counting detectors split the X-ray beam into its component energies or spectrum bins and count a number of photons in each of the bins. Since spectral CT involves the detection of transmitted X-rays at two or more energy levels, spectral CT generally includes dual-energy CT by definition.
Many clinical applications can benefit from spectral CT technology, which can provide improvement in material differentiation and beam hardening correction. Further, semiconductor-based photon-counting detectors are a promising candidate for spectral CT, which is capable of providing better spectral information compared with conventional spectral CT technology (e.g., dual-source, kVp-switching, etc.).
Photon-counting detectors are configured to acquire the spectral nature of the X-ray source. To obtain the spectral nature of the transmitted X-ray data, the photon-counting detector counts a number of photons in each of a plurality of energy bins. The use of the spectral nature of the X-ray source in CT is often referred to as spectral CT. Since spectral CT involves the detection of transmitted X-rays at two or more energy levels, spectral CT generally includes dual-energy CT by definition.
Semiconductor based photon-counting detectors used in spectral CT can detect incident photons and measure photon energy for every event. However, due to factors such as interaction depth and ballistic deficit, the measured photon energy cannot be related to incident photon energy uniquely. Furthermore, at high flux, pulse-pileup may also cause a loss in photon count and a distortion in photon energy. Accordingly, accurate image reconstruction can be achieved by efficiently estimating parameters of a response function of the photon-counting detectors.
There are several effects that can cause the detected spectrum to deviate from the X-ray spectrum incident on the photon-counting detectors, including: pileup (i.e., multiple detection events occurring within the detector response time), ballistic deficit effects, polar effects, characteristic X-ray escape, and space-charge effects.
Regarding pileup and ballistic deficit, due to the dead time (˜100 ns), which is determined by the type of semiconductor (e.g. CZT or Cd Te), the semiconductor thickness and readout circuitry, pulse pileup at high X-ray flux (˜108 cps/mm2) can be very severe, and the measured spectral signals can be distorted. The distorted spectral signal can cause artifacts in the reconstructed images. Furthermore, the dead time is not a constant for a given readout circuit due to the location of the pulse formation within the detector cell. However, if the pileup effect can be corrected in the detector model, then image quality can be improved.
Regarding the polar effect, when X-ray radiation is incident on a detector element at an oblique angle rather than normal incidence, then X-rays will enter the detector element through multiple faces of the detector element. The pileup and ballistic deficit will depend on which face the X-rays enter through. Thus, a detector response model benefits from including the differences in the pileup and ballistic deficit due to oblique X-rays illuminating multiple faces of the detector (i.e., the polar effect).
Regarding characteristic X-ray escape, when high energy photons impinge on a detector, the inner shell electrons from atoms of the detector are ejected from the atom as “photoelectrons.” After the ionization or excitation, the atom is in an excited state with a vacancy (hole) in the inner electron shell. Outer shell electrons then fall into the created holes, thereby emitting photons with energy equal to the energy difference between the two states. Since each element has a unique set of energy levels, each element emits a pattern of X-rays characteristic of the element, termed “characteristic X-rays.” The intensity of the X-rays increases with the concentration of the corresponding element.
In many materials such as Cadmium Telluride (CdTe) or Cadmium Zinc Telluride (CZT) or the like, the characteristic X-rays primarily involve K-shell (closest shell to the nucleus of an atom) electrons. If the characteristic X-rays escape from the detector, the detector signal is incorrect and the loss of energy incurred manifests itself as errors in the output spectrum of the detectors. Thus, the measured spectral signal can be distorted and may cause artifacts in the reconstructed image.
Uncorrected, each of the discussed measurement/detector artifacts distorts the detected spectrum relative to the incident spectrum ultimately degrading the quality of reconstructed images and the material decomposition derived from the data.
One advantage of spectral CT, and spectral X-ray imaging in general, is that materials having atoms with different atomic number Z also have different spectral profiles for attenuation. Thus, by measuring the attenuation at multiple X-ray energies, materials can be distinguished and the attenuation can be attributed to a particular atom (i.e., effective Z). This attribution enables spectral projection data to be mapped from the spectral domain to the material domain using a material decomposition. In some instances, this material decomposition is performed using a dual-energy analysis method.
The dual-energy analysis method can be used because the attenuation of X-rays in biological materials is dominated by two physical processes (i.e., photoelectric absorption and Compton scattering). Thus, the attenuation coefficient as a function of energy can be approximated by the decompositionμ(E,x,y)=μPE(E,x,y)+μC(E,x,y),where μPE(E, x, y) is the photoelectric attenuation and μC(E, x, y) is the Compton attenuation. This attenuation coefficient can be rearranged instead into a decomposition of a high-Z material (i.e., material 1) and a low-Z material (i.e., material 2) to becomeμ(E,x,y)≈μ1(E)c1(x,y)+μ2(E)c2(x,y),wherein c1,2(x,y) are spatial functions describing how much the imaged object located at position (x,y) is represented by materials 1 and 2, respectively.